Prediction of post-stroke dementia using NINDS-CSN 5-minute neuropsychology protocol in acute stroke

Blood biomarkers for post-stroke cognitive impairment: A systematic review and meta-analysis

BACKGROUND AND PURPOSE

Post-stroke cognitive impairment (PSCI) is a frequent consequence of stroke, which affects the quality of life and prognosis of stroke survivors. Numerous studies have indicated that blood biomarkers may be the key determinants for predicting and diagnosing cognitive impairment, but the results remain varied. Therefore, this meta-analysis aims to summarize potential biomarkers associated with PSCI.

METHODS

PubMed, Web of Science, Embase, and Cochrane Library were comprehensively searched for studies exploring blood biomarkers associated with PSCI from inception to 15 April 2022.

RESULTS

63 studies were selected from 4,047 references, which involves 95 blood biomarkers associated with the PSCI. We meta-analyzed 20 potential blood biomarker candidates, the results shown that the homocysteine (Hcy) (SMD = 0.35; 95 %CI: 0.20-0.49; P < 0.00001), c-reactive protein (CRP) (SMD = 0.49; 95 %CI: 0.20-0.78; P = 0.0008), uric acid (UA) (SMD = 0.41; 95 %CI: 0.06-0.76; P = 0.02), interleukin 6 (IL-6) (SMD = 0.92; 95 % CI: 0.27-1.57; P = 0.005), cystatin C (Cys-C) (SMD = 0.58; 95 %CI: 0.28-0.87; P = 0.0001), creatinine (SMD = 0.39; 95 %CI: 0.23-0.55; P < 0.00001) and tumor necrosis factor alpha (TNF-α) (SMD = 0.45; 95 %CI: 0.08-0.82; P = 0.02) levels were significantly higher in patients with PSCI than in the non-PSCI group.

CONCLUSION

Based on our findings, we recommend that paramedics focus on the blood biomarkers levels of Hcy, CRP, UA, IL-6, Cys-C, creatinine and TNF-α in conjunction with neuroimaging and neuropsychological assessment to assess the risk of PSCI, which may help with early detection and timely preventive measures. At the same time, other potential blood biomarkers should be further validated in future studies.

Neuropsychiatric and cognitive symptoms in people with hypertension: An examination with the NINDS-CSN consensus protocol

Hypertension has been associated with risk of cognitive impairments. The American Heart Association recommended the use of the harmonized neuropsychological protocol suggested by the National Institute of Neurologic Disorders and Stroke and the Canadian Stroke Network (NINDS-CSN) for studying related cognitive impairments. Initially designed for vascular cognitive impairment, empirical data of results from NINDS-CSN protocol has not been well-established in hypertension. The present study recruited 58 adults diagnosed with hypertension and 44 normotensive controls. Tests from the NINDS-CSN protocol were given in three lengths, including neuropsychological tests and neuropsychiatric inventories. The results showed higher proportions of hypertensive adults with impairments on tests of memory and executive functions and that they performed worse as a group on several tests from the 30-minute protocol, but not on the other additional tests in the full-length version, nor on cognitive screening test in the 5-minute protocol such as the Mini-Mental State Examination or the Montreal Cognitive Assessment. There was no significant group difference on neuropsychiatric symptoms. These findings suggested that the 30-minute version of the NINDS-CSN protocol with the two supplemental tests was able to reveal selective cognitive deficits in hypertensive adults and provide a practical solution for related studies, balancing between the requirement of sensitivity, domain variety, and brevity.

Predicting post-stroke cognitive impairment using machine learning: A prospective cohort study

BACKGROUND

Post-stroke cognitive impairment (PSCI) is a serious complication of stroke that warrants prompt detection and management. Consequently, the development of a diagnostic prediction model holds clinical significance.

OBJECTIVE

Machine learning algorithms were employed to identify crucial variables and forecast PSCI occurrence within 3-6 months following acute ischemic stroke (AIS).

METHODS

A prospective study was conducted on a developed cohort (331 patients) utilizing data from the Affiliated Zhongda Hospital of Southeast University between January 2022 and August 2022, as well as an external validation cohort (66 patients) from December 2022 to January 2023. The optimal model was determined by integrating nine machine learning classification models, and personalized risk assessment was facilitated by a Shapley Additive exPlanations (SHAP) interpretation.

RESULTS

Age, education, baseline National Institutes of Health Scale (NIHSS), Cerebral white matter degeneration (CWMD), Homocysteine (Hcy), and C-reactive protein (CRP) were identified as predictors of PSCI occurrence. Gaussian Naïve Bayes (GNB) model was determined to be the optimal model, surpassing other classifier models in the validation set (area under the curve [AUC]: 0.925, 95 % confidence interval [CI]: 0.861 - 0.988) and achieving the lowest Brier score. The GNB model performed well in the test sets (AUC: 0.919, accuracy: 0.864, sensitivity: 0.818, and specificity: 0.932).

CONCLUSIONS

The present study involved the development of a GNB model and its elucidation through employment of the SHAP method. These findings provide compelling evidence for preventing PSCI, which could serve as a guide for high-risk patients to undertake appropriate preventive measures.

Machine learning in the prediction of post-stroke cognitive impairment: a systematic review and meta-analysis

Objective

Cognitive impairment is a detrimental complication of stroke that compromises the quality of life of the patients and poses a huge burden on society. Due to the lack of effective early prediction tools in clinical practice, many researchers have introduced machine learning (ML) into the prediction of post-stroke cognitive impairment (PSCI). However, the mathematical models for ML are diverse, and their accuracy remains highly contentious. Therefore, this study aimed to examine the efficiency of ML in the prediction of PSCI.

Methods

Relevant articles were retrieved from Cochrane, Embase, PubMed, and Web of Science from the inception of each database to 5 December 2022. Study quality was evaluated by PROBAST, and c-index, sensitivity, specificity, and overall accuracy of the prediction models were meta-analyzed.

Results

A total of 21 articles involving 7,822 stroke patients (2,876 with PSCI) were included. The main modeling variables comprised age, gender, education level, stroke history, stroke severity, lesion volume, lesion site, stroke subtype, white matter hyperintensity (WMH), and vascular risk factors. The prediction models used were prediction nomograms constructed based on logistic regression. The pooled c-index, sensitivity, and specificity were 0.82 (95% CI 0.77-0.87), 0.77 (95% CI 0.72-0.80), and 0.80 (95% CI 0.71-0.86) in the training set, and 0.82 (95% CI 0.77-0.87), 0.82 (95% CI 0.70-0.90), and 0.80 (95% CI 0.68-0.82) in the validation set, respectively.

Conclusion

ML is a potential tool for predicting PSCI and may be used to develop simple clinical scoring scales for subsequent clinical use.

Systematic Review Registration

https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=383476.

Incidence of post-stroke cognitive impairment in patients with first-ever ischemic stroke: a multicenter cross-sectional study in China

Background

Post-stroke cognitive impairment (PSCI) is a common sequela after stroke. China has a large population of stroke survivors, but a large-scale survey on the incidence and risk factors for PSCI has not been undertaken. We aimed to calculate the incidence and risk factors for vascular cognitive symptoms among first-ever stroke survivors in China through a multicenter cross-sectional study.

Methods

From May 1, 2019 to November 30, 2019, patients with a clinical diagnosis of first-ever ischemic stroke were recruited from 563 hospitalized-based stroke center networks in 30 provinces of China. Cognitive impairment was measured by 5-min National Institute of Neurological Disease and Stroke-Canadian Stroke Network (NINDS-CSN) at 3-6 months after the indexed stroke. Stepwise multivariate regression and stratified analysis were performed to assess the association between PSCI and demographic variables.

Findings

A total of 24,055 first-ever ischemic stroke patients were enrolled, with an average age of 70.25 ± 9.88 years. The incidence of PSCI as per the 5-min NINDS-CSN was 78.7%. Age ≥75 years old (OR: 1.887, 95%CI: 1.391-2.559), western regional residence (OR: 1.620, 95%CI: 1.411-1.860) and lower education level were associated with increased PSCI risk. Hypertension might be related to non-PSCI (OR: 0.832, 95%CI: 0.779-0.888). For patients under 45 years old, unemployment was an independent risk factor for PSCI (OR: 6.097, 95%CI: 1.385-26.830). For patients who were residents of the southern region (OR: 1.490, 95%CI: 1.185-1.873) and non-manual workers (OR: 2.122, 95%CI: 1.188-3.792), diabetes was related to PSCI.

Interpretation

PSCI is common in Chinese patients with first-ever stroke, and many risk factors are related to the occurrence of PSCI.

Funding

The Beijing Hospitals Authority Youth Program (No. QMS20200801); Youth Program of the National Natural Science Foundation of China (No. 81801142); the Key Project of Science and Technology Development of China Railway Corporation (No. K2019Z005); The Capital Health Research and Development of Special (No. 2020-2-2014); Science and Technology Innovation 2030-Major Project (No. 2021ZD0201806).

Assessment of cognitive impairment after acute cerebral infarction with T1 relaxation time measured by MP2RAGE sequence and cerebral hemodynamic by transcranial Doppler

Objective

This study aimed to investigate early brain microstructural changes discovered using magnetization-prepared two rapid acquisition gradient echo (MP2RAGE) sequence and cerebral hemodynamic using TCD for cognitive impairment after acute cerebral infarction.

Methods

We enrolled 43 patients with acute cerebral infarction and 21 healthy people in the study, who were subjected to cognitive assessments, the MP2RAGE sequence, and a cerebral hemodynamic examination. A total of 26 brain regions of interest were investigated. Furthermore, we used cerebral hemodynamics to explain brain microstructural changes, which helped us better understand the pathophysiology of cognitive impairment after acute cerebral infarction and guide treatment.

Results

T1 relaxation times in the left frontal lobe, right frontal lobe, right temporal lobe, left precuneus, left thalamus, right hippocampus, right head of caudate nucleus, and splenium of corpus callosum were substantially different across the three groups, which were significantly correlated with neuropsychological test scores. CI group patients had significantly lower cerebral blood flow velocity than those in the N-CI and Normal groups. The receiver operating curve analysis revealed that most T1 relaxation times had high sensitivity and specificity, especially on the right temporal lobe and right frontal lobe. There was a potential correlation between T1 relaxation times and MMSE scores through TCD parameters.

Conclusion

The MP2RAGE sequence can detect alterations in whole brain microstructure in patients with cognitive impairment after acute cerebral infarction. Brain microstructural changes could influence cognitive function through cerebral hemodynamics. T1 relaxation times on the right temporal lobe and the right frontal lobe are expected to be a prospective biomarker of cognitive impairment after acute cerebral infarction.

The Liverpool Heart And bRain Project (L-HARP): Protocol for an Observational Cohort Study of Cardiovascular Risk and Outcomes Following Stroke

Further research is needed to refine risk prediction models for adverse cardiovascular outcomes following stroke in contemporary clinical practice, such as incident atrial fibrillation (AF), recurrent stroke, and cognitive impairment and dementia. The aims of this study are to prospectively investigate cardiovascular outcomes and risk factors for incident cardiovascular disease in a post-stroke cohort, and to externally validate, refine and expand current risk prediction models for cardiovascular and cardiovascular-related outcomes. The study sample size was based on the development of post-stroke risk prediction models for AF and was calculated as 1222 participants. The study design is a multicentre, prospective, observational cohort study. Participants will be adult patients admitted for ischaemic stroke confirmed by stroke physician or transient ischaemic attack (TIA) confirmed by MRI. Routinely collected data will be used in addition to the completion of simple validated questionnaires by the participants. Follow-up will be undertaken 12-months from the date of admission to hospital, in addition to linkage to routinely collected follow-up hospitalisation and mortality data. The primary outcomes are cardiovascular outcomes (including incident AF, stroke, TIA and myocardial infarction) at 12-month follow-up, all-cause mortality and mortality from cardiovascular causes, and incident cognitive impairment and dementia. Secondary outcomes include changes in function, depression, anxiety, fatigue and quality of life. The study has received approval from the Health Research Authority Research Ethics Committee (21/WA/0209), and is registered on https://www.clinicaltrials.gov/ (Identifier NCT05132465). Recruitment for the study began in October 2021 with completion of recruitment at all participating centres anticipated by October 2022.

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Post-Stroke Cognitive Impairment and Dementia

Poststroke cognitive impairment and dementia (PSCID) is a major source of morbidity and mortality after stroke worldwide. PSCID occurs as a consequence of ischemic stroke, intracerebral hemorrhage, or subarachnoid hemorrhage. Cognitive impairment and dementia manifesting after a clinical stroke is categorized as vascular even in people with comorbid neurodegenerative pathology, which is common in elderly individuals and can contribute to the clinical expression of PSCID. Manifestations of cerebral small vessel disease, such as covert brain infarcts, white matter lesions, microbleeds, and cortical microinfarcts, are also common in patients with stroke and likewise contribute to cognitive outcomes. Although studies of PSCID historically varied in the approach to timing and methods of diagnosis, most of them demonstrate that older age, lower educational status, socioeconomic disparities, premorbid cognitive or functional decline, life-course exposure to vascular risk factors, and a history of prior stroke increase risk of PSCID. Stroke characteristics, in particular stroke severity, lesion volume, lesion location, multiplicity and recurrence, also influence PSCID risk. Understanding the complex interaction between an acute stroke event and preexisting brain pathology remains a priority and will be critical for developing strategies for personalized prediction, prevention, targeted interventions, and rehabilitation. Current challenges in the field relate to a lack of harmonization of definition and classification of PSCID, timing of diagnosis, approaches to neurocognitive assessment, and duration of follow-up after stroke. However, evolving knowledge on pathophysiology, neuroimaging, and biomarkers offers potential for clinical applications and may inform clinical trials. Preventing stroke and PSCID remains a cornerstone of any strategy to achieve optimal brain health. We summarize recent developments in the field and discuss future directions closing with a call for action to systematically include cognitive outcome assessment into any clinical studies of poststroke outcome.

Post-Stroke Cognitive Impairment: Epidemiology, Risk Factors, and Management

Stroke, characterized as a neurological deficit of cerebrovascular cause, is very common in older adults. Increasing evidence suggests stroke contributes to the risk and severity of cognitive impairment. People with cognitive impairment following stroke often face with quality-of-life issues and require ongoing support, which have a profound effect on caregivers and society. The high morbidity of post-stroke cognitive impairment (PSCI) demands effective management strategies, in which preventive strategies are more appealing, especially those targeting towards modifiable risk factors. In this review article, we attempt to summarize existing evidence and knowledge gaps on PSCI: elaborating on the heterogeneity in current definitions, reporting the inconsistent findings in PSCI prevalence in the literature, exploring established or less established predictors, outlining prevention and treatment strategies potentially effective or currently being tested, and proposing promising directions for future research.

A Nationwide Multi-Center Questionnaire Survey on the Real-World State and Clinical Management of Poststroke Dementia in Japan

Background:

Poststroke dementia (PSD) is a serious problem for stroke survivors. However, there is still limited data on the real-world state and clinical management of PSD worldwide, and several countries already have a super-aged society.

Objective:

We conducted a nationwide questionnaire survey to examine the real-world state and management of PSD in Japan.

Methods:

A survey was conducted in the top 500 Japanese hospitals regarding the number of stroke patients treated between July 2018 and August 2019. Thirteen questions regarding PSD were mailed to doctors responsible for stroke management.

Results:

Responses were obtained from 251 hospitals (50.2%). The chief doctors responsible for stroke management answered the questionnaires. The median numbers of patients admitted annually with stroke in the departments of neurology and neurosurgery in the hospitals were 281.0 (interquartile range [IQR], 231.8–385.3) and 253.5 (IQR, 210.0–335.3), respectively, and most hospitals were acute care hospitals. Executive dysfunction was the most common cognitive dysfunction (10.9%), followed by amnesia (9.5%) and apathy (4.1%). Surprisingly, many stroke survivors lived alone at home (23.7%). Montreal Cognitive Assessment was significantly uncommon compared to Mini-Mental State Examination (p < 0.01). Furthermore, objective evaluation tests for behavioral and psychological symptoms of dementia were not often performed. Cognitive rehabilitation treatments were performed more often and earlier than drug treatments. The first drug of choice for PSD was predominantly donepezil (79.1%), followed by galantamine (6.1%), cilostazol (4.9%), memantine (2.5%), and rivastigmine (1.8%).

Conclusion:

Our study provides real-world evidence for the state of clinical practice related to PSD in Japan.

Development and validation of a clinical model (DREAM-LDL) for post-stroke cognitive impairment at 6 months

Introduction: This multicenter, retrospective study assessed the prevalence of post-stroke cognitive impairment (PSCI) 6 months after acute ischemic stroke (AIS) and its risk factors to build a bedside early predictive model for PSCI using the Montreal Cognitive Assessment (MoCA).

Methods: Records of consecutive patients with AIS treated at 4 stroke centers in Shanghai had MoCA assessments within 2 weeks after AIS onset and 6 months later were reviewed. Prevalence of PSCI (MoCA<22) was calculated and risk factors were identified by multivariate logistic regression analysis. The modeling and validation and identified risk factors were included in a predictive model using multivariate regression.

Results: There were 383 patients included and prevalence of PSCI 6 months after AIS was 34.2%, significantly lower than prevalence of patients with acute cognitive impairment (49.6%). Aging, less education, higher glucose level and severe stroke were PSCI risk factors, while level of low-density lipoprotein cholesterol (LDL-C) had a paradox effect on the risk of PSCI. 40.0% of the patients with cognitive impairment at acute phase reverted to normal, and patients with LDL-C 1.8-2.5 mmol/L were more likely to revert. The predictive model we built, DREAM-LDL (Diabetes [fasting blood glucose level], Rating [NIHSS], level of Education, Age, baseline MoCA and LDL-C level), had an AUROC of 0.93 for predicting PSCI at 6 months.

Conclusion: PSCI was common among AIS patients 6 months after AIS. We provided a practical tool to predict PSCI based on MoCA and risk factors present during acute phase of AIS.

Current Update on the Clinical Utility of MMSE and MoCA for Stroke Patients in Asia: A Systematic Review

Objective: Primary care clinicians in Asia employed the Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA) to aid dementia diagnosis post-stroke. Recent studies questioned their clinical utility in stroke settings for relying on verbal abilities and education level, as well as lack of consideration for aphasia and neglect. We aimed to review the clinical utility of the MMSE and MoCA for stroke patients in Asia and provide recommendations for clinical practice. Methods: PubMed, Scopus, Web of Science, and Science Direct were searched for relevant articles. Included studies were assessed for risk of bias. RevMan 5.4 was used for data synthesis (sensitivity and specificity) and covariates were identified. Results: Among the 48 full-text articles reviewed, 11 studies were included with 3735 total subjects; of these studies, 7 (77%) were conducted in China, 3 (27%) in Singapore, and 1 (9%) in South Korea. Both the MMSE and MoCA generally showed adequate sensitivity and specificity. Education was identified as a covariate that significantly affected detection accuracy. Due to heterogeneity in cutoff scores, methodologies, and languages, it was not feasible to suggest a single cutoff score. One additional point is recommended for MoCA for patients with <6 years of education. Conclusion: Clinicians in Asia are strongly recommended to consider the education level of stroke patients when interpreting the results of the MMSE and MoCA. Further studies in other Asian countries are needed to understand their clinical value in stroke settings.

Risk Prediction of Cognitive Decline after Stroke

BACKGROUND AND PURPOSE

Cognitive decline is one of the major outcomes after stroke. We have developed and evaluated a risk predictive tool of post-stroke cognitive decline and assessed its clinical utility.

METHODS

In this population-based cohort, 4,783 patients with first-ever stroke from the South London Stroke Register (1995-2010) were included in developing the model. Cognitive impairment was measured using the Mini Mental State Examination (cut off 24/30) and the Abbreviated Mental Test (cut off 8/10) at 3-months and yearly thereafter. A penalised mixed-effects linear model was developed and temporal-validated in a new cohort consisted of 1,718 stroke register participants recruited from (2011-2018). Prediction errors on discrimination and calibration were assessed. The clinical utility of the model was evaluated using prognostic accuracy measurements and decision curve analysis.

RESULTS

The overall predictive model showed good accuracy, with root mean squared error of 0.12 and R2 of 73%. Good prognostic accuracy for predicting severe cognitive decline was observed AUC: (88%, 95% CI [85-90]), (89.6%, 95% CI [86-92]), (87%, 95% CI [85-91]) at 3 months, one and 5 years respectively. Average predicted recovery patterns were analysed by age, stroke subtype, Glasgow-coma scale, and left-stroke and showed variability. DECISION: curve analysis showed an increased clinical benefit, particularly at threshold probabilities of above 15% for predictive risk of cognitive impairment.

CONCLUSIONS

The derived prognostic model seems to accurately screen the risk of post-stroke cognitive decline. Such prediction could support the development of more tailored management evaluations and identify groups for further study and future trials.

Development of a short-form Swedish version of the Montreal Cognitive Assessment (s-MoCA-SWE): protocol for a cross-sectional study

INTRODUCTION

Short forms of the Montreal Cognitive Assessment (MoCA) have allowed quick cognitive screening. However, none of the available short forms has been created or validated in a Swedish sample of patients with stroke.The aim is to develop a short-form Swedish version of the MoCA (s-MoCA-SWE) in a sample of patients with acute and subacute stroke. The specific objectives are: (1) to identify a subgroup of MoCA items that have the potential to form the s-MoCA-SWE; (2) to determine the optimal cut-off value of s-MoCA-SWE for predicting cognitive impairment and (3) and to compare the psychometric properties of s-MoCA-SWE with those of previously developed MoCA short forms.

METHODS AND ANALYSIS

This is a statistical analysis protocol for a cross-sectional study. The study sample will comprise patients from Väststroke, a local stroke registry from Gothenburg, Sweden and Efficacy oF Fluoxetine-a randomisEd Controlled Trial in Stroke (EFFECTS), a randomised controlled trial in Sweden. The s-MoCA-SWE will be developed by using exploratory factor analysis and the boosted regression tree algorithm. The cut-off value of s-MoCA-SWE for impaired cognition will be determined based on binary logistic regression analysis. The psychometric properties of s-MoCA-SWE will be compared with those of other MoCA short forms by using cross-tabulation and area under the receiving operating characteristic curve analyses.

ETHICS AND DISSEMINATION

The Väststroke study has received ethical approval from the Regional Ethical Review Board in Gothenburg (346-16) and the Swedish Ethical Review Authority (amendment 2019-04299). The handling of data generated within the framework of quality registers does not require written informed consent from patients. The EFFECTS study has received ethical approval from the Stockholm Ethics Committee (2013/1265-31/2 on 30 September 2013). All participants provided written consent. Results will be published in an international, peer-reviewed journal, presented at conferences and communicated to clinical practitioners in local meetings and seminars.

Concurrent validity of the short version of Montreal Cognitive Assessment (MoCA) for patients with stroke

The aim of the present study was to examine the concurrent validity of 2 Chinese versions of the short version of the Montreal Cognitive Assessment (MoCA) in patients with stroke, i.e., MoCA 5-minute protocol and National Institute for Neurological Disorders and Stroke and Canadian Stroke Network (NINDS-CSN) 5-minute Protocol. A total of 54 patients and 27 healthy controls were enrolled in this study. In this study, the Neurobehavioural Cognitive Status Examination (NCSE) was used as an external criterion of cognitive impairment. We found that the 5-min protocol did not differ from the MoCA in differentiating patients with cognitive impairments from those without (area under the receiver operating characteristic curve, AUC, of 0.948 for the MoCA 5-min protocol v.s. 0.984 for MoCA, P = 0.097). These three assessments demonstrated equal performance in differentiating patients with stroke from controls. The Chinese version of the MoCA 5-min protocol can be used as a valid screening for patients with stroke.

Enriched Environment Promotes Cognitive Function Recovery following Cerebral Ischemic Injury via Upregulating GABAergic and Glutamatergic Systems in the Contralateral Hippocampus

Poststroke cognitive impairment severely affects the long-term recovery of patients. However, it remains unknown whether an enriched environment can remodel contralateral hippocampal function and promote cognitive function recovery after cerebral ischemic injury. To further explore, 36 C57BL/6 mice that underwent permanent middle cerebral artery occlusion (pMCAO) were randomly assigned to three groups: enriched environment (EE), standard condition (SC), and sham surgery (Sham). After 21 days of intervention, the Morris water maze and step-through test was utilized for testing the cognitive function of the mice, cresyl violet staining for measuring the degree of atrophy in the hippocampal tissues, and western blotting for quantitating the expression levels of GA1B, GAD67, and NR2B, and immunohistochemistry for levels of NR2B in the CA1 region of the contralateral hippocampus. The results showed that cognitive function-related behavioral performance decreased in the SC group, and performance was better in the EE group than that in the SC group (p < 0.01); no significant difference in the degree of contralateral cerebral atrophy was observed between the EE and SC groups (p > 0.05); levels of GA1B, GAD67, and NR2B in the contralateral hippocampus were significantly higher in the EE group than those in the SC group (p < 0.01); and the level of NR2B in the CA1 region of the contralateral hippocampus significantly increased in the EE group compared to the SC group (p < 0.01). We believe that contralateral hippocampal function is inhibited after cerebral ischemic injury, further affecting cognitive function. However, enriched environment can upregulate GABAergic and glutamatergic systems in the contralateral hippocampus to promote cognitive function recovery after cerebral ischemic injury.

Comparative Study of Two Short-Form Versions of the Montreal Cognitive Assessment for Screening of Post-Stroke Cognitive Impairment in a Chinese Population

Purpose

Cognitive impairment (CI) is one of the most significant post-stroke complications. The Montreal Cognitive Assessment (MoCA) is widely applied to the early screening of post-stroke CI (PSCI), and has good sensitivity and specificity, but needs a long time to administer. Clinicians and researchers need shorter, more effective cognitive testing tools. The purpose of this study was to detect the sensitivity and specificity of two different short-form versions of the MoCA (SF-MoCA) for screening of PSCI in a Chinese population.

Methods

A total of 2,989 stroke participants were included from 14 hospitals in northern and southern China between June 2011 and September 2013. The sensitivity and specificity of the two SF-MoCA versions were compared.

Results

Using an MoCA score <26 as the critical value, the National Institute of Neurological Disease and Stroke–Canadian Stroke Network SF-MoCA showed sensitivity of 91% and specificity of 63% (PPV 71%, BPV 87%) with scores ≤10 points. The sensitivity and specificity of the Bocti SF-MoCA were 92% and 69% (PPV 75%, BPV 89%) with scores ≤7, respectively. The area under the curve was 0.885 (95% CI 0.873–0.897) and 0.912 (95% CI 0.902–0.922), respectively.

Conclusion

The Bocti SF-MoCA can be used as a briefer and more effective screening tool for PSCI in Chinese.

Psychometric Properties of the National Institute of Neurological Disorders and Stroke and Canadian Stroke Network Neuropsychological Battery in an Asian Older Adult Sample

OBJECTIVE

Despite the wide usage of the National Institute of Neurological Disorders and Stroke and Canadian Stroke Network (NINDS-CSN) neuropsychological battery for the detection of vascular cognitive impairment, its reliability and validity have not been established. Therefore, the present study established the psychometric properties of the battery in cognitively normal older adults in a clinical setting in Singapore.

DESIGN

Longitudinal study.

SETTING AND PARTICIPANTS

A total of 105 cognitively normal older adults age 50 years and older were assessed in a memory clinic setting.

METHODS

The 60-minute NINDS-CSN and 5-minute protocol were administered to participants at baseline and 3-month follow-up. Raw scores were transformed into standardized z scores. Test-retest reliability, concurrent validity and construct (convergent and discriminant) validity were reported.

RESULTS

Moderate-to-excellent test-retest reliability (r = 0.36-0.87), concurrent validity, and construct validity (r = 0.41-0.83) were found in both protocols over 3 months (all Ps < 0.01). Although the 5-minute protocol showed moderate validity (r = 0.41), the 60-minute protocol had excellent concurrent validity against a locally validated neuropsychological battery (r = 0.83).

CONCLUSION AND IMPLICATIONS

The NINDS-CSN is reliable and valid in assessing cognitive function. The 60-minute protocol demonstrates great utility beyond its current usage in vascular cognitive impairment populations to the general older adult population. The 5-minute protocol can be used as a brief cognitive screening tool in primary healthcare and the community, due to its brevity and accuracy. Future research should further examine the generalizability of the NINDS-CSN battery in other dementias and cognitive disorders.

Cognitive impairment and medication adherence post-stroke: A five-year follow-up of the ASPIRE-S cohort

BACKGROUND

Control of vascular risk factors is essential for secondary stroke prevention. However, adherence to secondary prevention medications is often suboptimal, and may be affected by cognitive impairment. Few studies to date have examined associations between cognitive impairment and medication adherence post-stroke, and none have considered whether adherence to secondary prevention medications might affect subsequent cognitive function. The aim of this study was to explore prospective associations between cognitive impairment and medication non-adherence post-stroke.

METHODS

A five-year follow-up of 108 stroke survivors from the Action on Secondary Prevention Interventions and Rehabilitation in Stroke (ASPIRE-S) prospective observational cohort study. Cognitive function was assessed using the Montreal Cognitive Assessment at 6 months, and a neuropsychological test battery at 5 years. Adherence to antihypertensive, antithrombotic and lipid-lowering medications was assessed using prescription refill data.

RESULTS

The prevalence of cognitive impairment at five years was 35.6%. The prevalence of non-adherence ranged from 15.1% for lipid-lowering agents to 30.2% for antithrombotics. There were no statistically significant associations between medication non-adherence in the first year post-stroke and cognitive impairment at 5 years, nor between cognitive impairment at 6 months and non-adherence at 5 years. Stroke survivors with cognitive impairment were significantly more likely to report receiving help with taking medications [OR (95% CI): 4.84 (1.17, 20.07)].

CONCLUSIONS

This is the first study to explore the potential impact of non-adherence to secondary prevention medications on cognitive impairment in stroke survivors. Findings highlight the role of family members and caregivers in assisting stroke survivors with medication administration, particularly in the context of deficits in cognitive function. Involving family members and caregivers may be a legitimate and cost-effective strategy to improve medication adherence in stroke survivors.

Accuracy of the short-form Montreal Cognitive Assessment: Systematic review and validation

INTRODUCTION

Short-form versions of the Montreal Cognitive Assessment (SF-MoCA) are increasingly used to screen for dementia in research and practice. We sought to collate evidence on the accuracy of SF-MoCAs and to externally validate these assessment tools.

METHODS

We performed systematic literature searching across multidisciplinary electronic literature databases, collating information on the content and accuracy of all published SF-MoCAs. We then validated all the SF-MoCAs against clinical diagnosis using independent stroke (n = 787) and memory clinic (n = 410) data sets.

RESULTS

We identified 13 different SF-MoCAs (21 studies, n = 6477 participants) with differing test content and properties. There was a pattern of high sensitivity across the range of SF-MoCA tests. In the published literature, for detection of post stroke cognitive impairment, median sensitivity across included studies: 0.88 (range: 0.70-1.00); specificity: 0.70 (0.39-0.92). In our independent validation using stroke data, median sensitivity: 0.99 (0.80-1.00); specificity: 0.40 (0.14-0.87). To detect dementia in older adults, median sensitivity: 0.88 (0.62-0.98); median specificity: 0.87 (0.07-0.98) in the literature and median sensitivity: 0.96 (range: 0.72-1.00); median specificity: 0.36 (0.14-0.86) in our validation. Horton's SF-MoCA (delayed recall, serial subtraction, and orientation) had the most favorable properties in stroke (sensitivity: 0.90, specificity: 0.87, positive predictive value [PPV]: 0.55, and negative predictive value [NPV]: 0.93), whereas Cecato's "MoCA reduced" (clock draw, animal naming, delayed recall, and orientation) performed better in the memory clinic (sensitivity: 0.72, specificity: 0.86, PPV: 0.55, and NPV: 0.93).

CONCLUSIONS

There are many published SF-MoCAs. Clinicians and researchers using a SF-MoCA should be explicit about the content. For all SF-MoCA, sensitivity is high and similar to the full scale suggesting potential utility as an initial cognitive screening tool. However, choice of SF-MoCA should be informed by the clinical population to be studied.

Longitudinal Effect of Stroke on Cognition: A Systematic Review

BACKGROUND

Stroke is associated with an increased risk of dementia; however, the impact of stroke on cognition has been found to be variable, such that stroke survivors can show decline, remain stable, or revert to baseline cognitive functioning. Knowing the natural history of cognitive impairment after stroke is important for intervention. The aim of this systematic review is to investigate the longitudinal course of cognitive function in stroke survivors.

METHODS AND RESULTS

Three electronic databases (Medline, Embase, PsycINFO) were searched using OvidSP from inception to July 15, 2016. Longitudinal studies with ≥2 time points of cognitive assessment after stroke were included. In total, 5952 articles were retrieved and 14 were included. There was a trend toward significant deterioration in cognitive test scores in stroke survivors (8 studies). Cognitive stability (3 studies) and improvement (3 studies) were also demonstrated, although follow-up time tended to be shorter in these studies. Variables associated with impairment included age, ethnicity, premorbid cognitive performance, depression, stroke location, and history of previous stroke. Associations with APOE*E4 (apolipoprotein E with the E4 allele) allele status and sex were mixed.

CONCLUSIONS

Stroke is associated with an increased risk of cognitive decline, but cognitive decline is not a consequence. Factors associated with decline, such as sociodemographic status, health-related comorbidity, stroke history, and clinical features could be used in models to predict future risk of dementia after stroke. A risk model approach could identify patients at greatest risk for timely intervention to reduce the frequency or delay the onset of poststroke cognitive impairment and dementia.